Structuur en dynamiek van diaglossische taalrepertoria: een pleidooi voor meer empirisch onderzoek

In this paper, it is shown that the language repertoire in Flanders is in need of thorough macro-research. In the last decades, many researchers have focused on the form and function of parts of the diaglossic language repertoire, such as the Flemish dialects, the standard language and what is called tussentaal (‘in-between-language’). While these studies have yielded interesting sociolinguistic insights in aspects of the linguistic repertoire, they often tend to neglect the macro level, hence leaving several questions about the language repertoire in Flanders and by extension about repertoires in general unanswered. The present paper tracks some key lacunae in the current literature on the structure of the Flemish diaglossic situation, continuing with a status quaestionis about its dynamics. This double overview will ground a plea for more empirical research into language repertoires as macro-entities. To conclude, a concrete example will be given of how such empirical research might be conducted, taken from a project at Ghent University on the Flemish language repertoire

Combining Linear Logic and Size Types for Implicit Complexity

Several type systems have been proposed to statically control the time complexity of lambda-calculus programs and characterize complexity classes such as FPTIME or FEXPTIME. A first line of research stems from linear logic and restricted versions of its !-modality controlling duplication. A second approach relies on the idea of tracking the size increase between input and output, and together with a restricted recursion scheme, to deduce time complexity bounds. However both approaches suffer from limitations : either a limited intensional expressivity, or linearity restrictions. In the present work we incorporate both approaches into a common type system, in order to overcome their respective constraints. Our system is based on elementary linear logic combined with linear size types, called sEAL, and leads to characterizations of the complexity classes FPTIME and 2k-FEXPTIME, for k >= 0

Measuring comprehension and perception of neural machine translated texts : a pilot study

In this paper we compare the results of reading comprehension tests on both human translated and raw (unedited) machine translated texts. We selected three texts of the English Machine Translation Evaluation version (CREG-MT-eval) of the Corpus of Reading Comprehension Exercises (CREG), for which we produced three different translations: a manual translation and two automatic translations generated by two state-of-the-art neural machine translation engines, viz. DeepL and Google Translate. The experiment was conducted via a SurveyMonkey questionnaire, which 99 participants filled in. Participants were asked to read the translation very carefully after which they had to answer the comprehension questions without having access to the translated text. Apart from assessing comprehension, we posed additional questions to get information on the participants’ perception of the machine translations. The results show that 74% of the participants can tell whether a translation was produced by a human or a machine. Human translations received the best overall clarity scores, but the reading comprehension tests provided much less unequivocal results. The errors that bother readers most relate to grammar, sentence length, level of idiomaticity and incoherence

'Handhavers van de norm' of 'taalamateurs': spreken leerkrachten beter Nederlands dan andere hoogopgeleiden?

‘Elke leraar is een taalleraar’, stelde voormalig Vlaams minister van Onderwijs Frank Vandenbroucke toen hij in 2007 zijn taalbeleid uitwerkte. In zijn talenbeleidsnota (en die van zijn opvolger, Pascal Smet) werd het Standaardnederlands naar voren geschoven als de enige taalvariëteit die geschikt is om de problemen van taalachterstand en sociale ongelijkheid op school aan te pakken. Van Vlaamse leerkrachten wordt dan ook verwacht dat ze enkel standaardtaal gebruiken op school, niet alleen door het beleid, maar ook door de samenleving. Dat bleek recent nog toen de resultaten van de taaltest 'Hoe Vlaams is uw Nederlands?' (zie ook Over taal, januari-februari 2015) lieten zien dat leraren vrij tolerant zijn voor 'Vlaamse' elementen in de standaardtaal, en leerkrachten werden weggezet als ‘laks’, ‘slordig’, ‘onkundig’ en ‘taalamateurs’. Tegelijk worden leerkrachten wel vaak beschouwd als de handhavers van de standaardtaalnorm. Hoe zit het nu precies met dat standaardtaalgebruik van leerkrachten? Spreken zij inderdaad het ‘beste Nederlands’? In deze bijdrage proberen we op die vraag een antwoord te vinden, alsook op de vraag of er daarbij een verschil bestaat tussen leraren Nederlands en leraren van andere vakken